One of the principles for understanding data is that while some data contain signals, all data contain noise. Therefore, before you can detect the signals you’ll have to filter out the noise. This act of filtration is the essence of all data analysis techniques.

Staff meetings can be incredibly productive. Or unproductive—and more often the latter. If your staff meetings are terrible, it’s your fault because you’re not structuring them well.

From manufacturing and mining to hospitality and healthcare, computerized maintenance management systems (CMMS) have become all but essential.

In this article, I want to explore an idea that often is framed in moral terms but is actually a cybernetic imperative: the necessity of diversity for viable systems.

From the internet and smartphones to 3D printing, recent decades have ushered in general-purpose technology that increases efficiency and collapses the cost of routine tasks.

Your social media profile headline is nothing more than a phrase on a screen—a concise summary of your skills and expertise. But although that blurb gets you noticed, the real headline for executives is in how they lead.

In 2021, container ships idled for weeks outside the Port of Los Angeles, a stark visual reminder of just how fragile modern supply-chain reliability had become. The backlog sent shockwaves across industries.

The quality systems most medtech teams are stuck with aren’t built for how they work today. 21 CFR Part 820 was authorized by the Federal Food, Drug, and Cosmetic Act of 1978, long before the software industry even existed.

A young manager told me about the day she nearly quit her job. A major restructuring had left her team reeling. As targets shifted overnight, colleagues departed and rumors spread faster than facts.

What can we learn about human intelligence by studying how machines “think?” Can we better understand ourselves if we better understand the artificial intelligence systems that are becoming a more significant part of our everyday lives?